Cognitive Analytics Management: Digital Disruption for Innovative Shared Values

Call for papers for: Journal of Enterprise Information Management

Cognitive Analytics Management: Digital Disruption for Innovative Shared Values

BACKGROUND

Cognitive Analytics Management is a new relevant and rigorous interdisciplinary field. It is emerging from the demolishes of boundaries among scientific fields; the integration of concepts from artificial intelligence, business analytics, cognitive and behavioral science, data analytics, data engineering, data science, information systems, operations research and management; and the new advances in information and communication technologies and in computing power. It accelerates the digital transformation and disruption of every industry and every organization. It disrupts the traditional ways of processing things when addressing world challenges leading to new business models and innovations to boost productivity, to enhance competitiveness, to create shared values to all stakeholders for the sustainable development of our society and the world. Shared values are the combined shareholders’ business values and all stakeholders’ economic, environmental, social as well as other tangible and intangible outcome and impact values such as improved transparency and trust, eradication of corruption, continuous sustainable development among others.


A Cognitive Analytics Management (CAM) uses the following three processes of digital disruption technologies to transform all aspects of an organization:
•    A cognitive process frames a challenge in analytics terms. It enables asking the right questions to develop a digital strategy with a linkage to mission/vision and desired shared value goals to achieve. The digital strategy sets guidelines for building data architecture models, respecting data protection and privacy regulation, collecting real data for validated variables using cognitive agents, cognitive services and internet of things to data technology tools.
•    The analytics process analyzes the generated real data using descriptive, predictive and prescriptive analytics to generate new digital insights and sentiments to make informed decisions, and to achieve the shared values to stakeholders. It employs methodologies inspired from various fields, including artificial intelligence, block-chains, behavioral psychology, data science, cognitive and cloud computing, big data analytics, data mining and deep machine learning, forecasting, management science, operations research, optimization, simulation, statistics and visualization, among others;
•    The management process advocates the necessary fundamental change management in an organization to empower digital leadership and talent to successfully embark on the digital transformation journey. Change of management is by far the most enduring bottleneck in the digital disruptive transformation. It requires a proper restructuring of organizations; empowering leadership to launch, accelerate, and implement analytics projects; and communicating shared values to stakeholders to achieve the sustainable development of organizations, society and the world.

CALL FOR PAPERS’ SUBMISSIONS

CAM processes are at the heart of digital disruption (transformation) in the fourth digital revolution era which is bringing many challenges, opportunities, failures and success stories. We seek high quality paper’s submissions which help in advancing the theoretical rigor, the excellence in practices and services of cognitive analytics management; and in setting the future research directions of our community.  Ideal papers should have a least two advanced contributions of the three CAM processes, with clear recommendations and insights, managerial implications, impacts and outcomes; See (Osman et al 2019).
IH Osman, AL Anouze, Z Irani, H Lee, TD Medeni, V Weerakkody. A cognitive analytics management framework for the transformation of electronic government services from users’ perspective to create sustainable shared values. European Journal of Operational Research, Volume 278, Issue 2, 16 October 2019, Pages 514-532. https://doi.org/10.1016/j.ejor.2019.02.018
Topics include but not limited to:
•    Cognitive Analytics Management Theories for Digital Disruptive and Innovative Shared Values– Barriers, Benefits, Challenges, Costs, Efficiency, Effectiveness, Opportunities, and Risks.
•    Cognitive Analytics Management Applications, Models and Implemented Technologies with real shared value impacts in the domain of applications: Business and Commerce, Economy, Logistics, Operations, Supply Chain in Health Care, Marketing..
•    Advance in emerging disruptive platforms and technologies including artificial intelligence, block-chain, big and open data,   machine learning, deep learning, quantum computing, cognitive services (internet of things, cognitive agents), cloud computing digital ecosystems, social media among others
•    New emerging initiatives and applications with potential impacts, outcomes, and implications of the digital disruptive/transformation in Business; Banking and Finance, Commerce and Retails, government,  Health –care and Medicine, Marketing,  Project/program and process, People , Supply chain & logistics; and poverty and humanitarian relief;  among others.
•    Digital transformation initiatives for fostering innovations and technology change management, Governance and ethical aspects, and performance in public and private organizations to create shared values, eradicate corruption, increase trust, loyalty and transparency in government among others.
•    Optimization, simulation, visualization models towards smart organizations (municipalities, cities, governments, organizations among others in the world).

SUBMISSION AND REVIEW PROCESS

Manuscripts should not have been previously published or be under review in other journals. Outstanding papers presented at Cognitive Analytics Management Conference 2018, CAM2018; International Conference on Digital Economy 2019, ICDEc2019, and are welcomed for submission. The guest editors also welcome submissions of high-quality papers from the research community at large. All authors are expected to explicitly state in their cover letter the contributions to the CAM processes. Submissions to the Journal of Enterprise Information Management are made using ScholarOne Manuscripts, the online submission and peer review system. The manuscript must comply with the author guidelines available on the Journal's page.


Authors must use the official JEIM submission portal and select ‘CAM’ special issue for their submission. We will accept online submissions until April 30 2020.

All papers will be screened by at least two guest editors (and desk rejected if not deemed suitable) before being sent to at least two referees. Papers will undergo a maximum of two rounds of revision to meet the scope and high standards of JEIM without any guarantee of final publication. We anticipate that the special issue will be published by the second half of 2020. For any queries regarding submission, please email the special issue guest editors.

Special Issue Guest Editors

Professor Ibrahim H. Osman, American University of Beirut, Lebanon: [email protected];
Dr Antoine Harfouche, EDHEC Business School, Paris, France: [email protected];Professor Stacie Petter, Hankamer School of Business, [email protected];Professor Rim Jallouli, University of Manouba, Tunis: [email protected]. Normal 0 false false false EN-US X-NONE AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-ansi-language:EN-US; mso-fareast-language:EN-US;}